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/*! \file
    \brief Template for a pipelined GEMM kernel. Does not compute batching or
   support split-K.
*/

#pragma once

#include "cutlass/cutlass.h"

#include "cutlass/aligned_buffer.h"
#include "cutlass/array.h"

#include "cutlass/numeric_types.h"
#include "cutlass/matrix_shape.h"

#include "cutlass/gemm/gemm.h"

/////////////////////////////////////////////////////////////////////////////////////////////////

namespace cutlass {
namespace gemm {
namespace kernel {

/////////////////////////////////////////////////////////////////////////////////////////////////

template <typename Mma, typename Epilogue, typename ThreadblockSwizzle>
__global__ void GemmPipelined(cutlass::gemm::GemmCoord problem_size,
                              cutlass::gemm::GemmCoord grid_tiled_shape,
                              typename Mma::IteratorA::Params params_A,
                              typename Mma::IteratorA::TensorRef ref_A,
                              typename Mma::IteratorB::Params params_B,
                              typename Mma::IteratorB::TensorRef ref_B,
                              typename Epilogue::Params params_epilogue) {
    // Shared storage needed by threadblock-scoped matrix multiply-accumulate
    __shared__ union {
        typename Mma::SharedStorage main_loop;
        typename Epilogue::SharedStorage epilogue;
    } shared_storage;

    // Compute threadblock location
    ThreadblockSwizzle threadblock_swizzle;

    cutlass::gemm::GemmCoord tb_tile_offset =
            threadblock_swizzle.get_tile_offset(grid_tiled_shape);

    if (grid_tiled_shape.m() <= tb_tile_offset.m() ||
        grid_tiled_shape.n() <= tb_tile_offset.n()) {
        return;
    }

    // Compute initial location in logical coordinates
    cutlass::MatrixCoord tb_offset_A{tb_tile_offset.m() * Mma::Shape::kM,
                                     tb_tile_offset.k()};

    cutlass::MatrixCoord tb_offset_B{tb_tile_offset.k(),
                                     tb_tile_offset.n() * Mma::Shape::kN};

    // Compute position within threadblock
    int tb_thread_id = threadIdx.x;

    // Construct iterators to A and B operands
    typename Mma::IteratorA iterator_A(params_A, ref_A.data(),
                                       {problem_size.m(), problem_size.k()},
                                       tb_thread_id, tb_offset_A);

    typename Mma::IteratorB iterator_B(params_B, ref_B.data(),
                                       {problem_size.k(), problem_size.n()},
                                       tb_thread_id, tb_offset_B);

    int warp_id = __shfl_sync(0xffffffff, threadIdx.x / 32, 0);
    int lane_id = threadIdx.x % 32;

    //
    // Main loop
    //

    // Construct thread-scoped matrix multiply
    Mma mma(shared_storage.main_loop, tb_thread_id, warp_id, lane_id);

    typename Mma::FragmentC accumulators;

    accumulators.clear();

    // Compute threadblock-scoped matrix multiply-add
    mma(problem_size, accumulators, iterator_A, iterator_B, accumulators);

    //
    // Epilogue
    //

    Epilogue epilogue(params_epilogue, shared_storage.epilogue, tb_thread_id,
                      warp_id, lane_id);

    tb_tile_offset = threadblock_swizzle.get_tile_offset(grid_tiled_shape);

    // assume identity swizzle
    MatrixCoord threadblock_offset(tb_tile_offset.m() * Mma::Shape::kM,
                                   tb_tile_offset.n() * Mma::Shape::kN);

    // run efficient epilogue
    epilogue({problem_size.m(), problem_size.n()}, accumulators,
             threadblock_offset);
}

/////////////////////////////////////////////////////////////////////////////////////////////////

}  // namespace kernel
}  // namespace gemm
}  // namespace cutlass
